Instructions to use hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fe2fe0719e58b43beaf42e506970f98f2d2084fe721f6fb5d2ea291f292b870
- Size of remote file:
- 889 kB
- SHA256:
- d4ea239bf5f81c1938e03ee4d1ce083b6feb6ec97dcf736d9abad047698cdd46
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